define-hypothesis

Hypothesis

A hypothesis is a testable prediction about how a change will affect user behavior or business outcomes. It transforms assumptions into explicit statements that can be validated or invalidated through experimentation. Well-formed hypotheses prevent teams from building features based on untested beliefs and create shared understanding of what success looks like.

When to Use

• After problem framing, before committing to a solution
• When designing experiments or A/B tests
• When team members have differing assumptions about user behavior
• Before investing significant engineering resources in a feature
• When pivoting direction and need to validate the new approach

When NOT to Use

• You are ready to design the actual A/B test (variants, sample size, duration) -> use measure-experiment-design; this skill frames what to test, not how
• The problem itself is still unframed -> use define-problem-statement first
• You want to organize many assumptions and ideas into a discovery structure -> use define-opportunity-tree
• The team needs the full business-model picture, not one testable claim -> use foundation-lean-canvas

Instructions

When asked to create a hypothesis, follow these steps:

1. State the Belief Articulate what you believe will happen. Use the structured format: "We believe that [action/change] for [target user] will [expected outcome]." Be specific about the intervention - vague hypotheses can't be tested.

2. Identify the Target User Define who this hypothesis applies to. A hypothesis about "users" is too broad. Specify the segment: new users in their first week, power users with 10+ sessions, churned users returning, etc.

3. Define the Expected Outcome What behavior change or result do you expect? Frame it in terms of user actions (complete onboarding, make a purchase, return within 7 days) rather than internal metrics when possible.